It is often desirable within a business or other planning environment to generate and/or analyze information regarding sales, demand, supply, selling price, or other data concerning a product or other item. Data for products may often be dependent in some manner on data for other hierarchically related products. For example, sales of products in a particular geographic region may be reflect sales for the products in a particular territory in the region. Because of these hierarchical dependencies, the data concerning various products or other items may be stored hierarchically in data storage or derived in a hierarchical fashion. Furthermore, the data may be stored at a storage location associated with multiple dimensions, such as a product dimension (the storage location being associated with a particular product or product component), a geography dimension (the storage location being associated with a particular geographical area), and a time dimension (the storage location being associated with a particular time or time period).
It is often desirable to select a subset of the members of a hierarchical dimension for use in a particular process (for example, to view planning data associated with particular products). The hierarchical dimensions reflect real world structures in the organization and these structures can change on a frequent basis. When members of a hierarchical dimension are added or deleted, have their position in the hierarchy changed, or have other characteristics changed on a frequent basis, a “hard coded” set of members used to perform a particular business process or function may quickly become out of date and have to be recreated. This process is time-consuming and inefficient and hampers the planning or other functions of a business.